Our overall objective is to significantly improve the efficacy and efficiency of image-guided neurosurgery for brain tumors by building a system to improve intraoperative visualization, navigation and monitoring. The system will create an augmented reality visualization of the intraoperative configuration of the patient's brain merged with high resolution preoperative imaging data, including diffusion tensor- and functional magnetic resonance imaging (DTIand fMRI), in order to better localize the tumor and critical healthy tissues. In current practice, the neurosurgeon acquires new intraoperative images in order to study the current configuration of the patient's brain and to monitor the progress of tumor resection. The first key limitation is that the neurosurgeon is required to make a subjective judgment as to when it is necessary to obtain a new volumetric acquisition. This involves a subjective estimate of the quality of navigation information available from the existing data based on the surgeon's assessment the amount of brain shift and tumor resection that has occurred since the last MRI was acquired. Furthermore, a second key limitation of existing state-of-the- art systems is an inability to present key preoperatively acquired data fused with the patient's intraoperative position when the brain has undergone significant deformation. Rather, the surgeon must mentally fuse the information from preoperative fMRI and DTI by mentally projecting it through the 3D spatial and temporal changes the patient's brain has undergone. We propose to develop, implement and evaluate novel algorithms to improve intraoperative navigation, targeting and visualization system for image-guided neurosurgery. We will shift from the current practice of infrequent subjectively timed whole brain intraoperative MRI acquisition to an objectively timed whole brain MRI supplemented with near real-time sparse imaging. The provision of near real-time updated visualizations of preoperative fMRI and DT-MRI fused with the patient's brain as brain shift occurs is expected to dramatically improve the capacity of the neurosurgeon to preserve eloquent cortex and functionally critical connectivity while maximizing the removal of tumor tissue. We will improve our model of brain deformation so that good alignment can be achieved for longer, encompassing larger brain deformations. This will help to overcome a significant limitation of intra- operative MRI: the need to interrupt surgery, move the patient, and extend operative time in order to acquire updated images. This project will contribute to public health by developing a system enabling accurate navigation during neurosurgery. This will provide more complete information to the neurosurgeon, aiding in the task of removing as much tumor as possible while minimizing the loss of healthy tissue.